7.8. Optimizing BACE1 Inhibitors with AIDD

7.8. Optimizing BACE1 Inhibitors with AIDD

Note: This tutorial requires an AIDD license. In addition, getting the results described here requires access to our PhysChem, Metabolism, and Toxicity Modules as well as to an HTPK license. If these are not available, you can run the tutorial with some alternative objective properties; just bear in mind that the results will differ from those described here. How much they differ will depend on exactly what the objectives used are.

This tutorial shows you how to perform a multi-objective AIDD optimization. The process generates a series of compounds, starting from a known BACE1 inhibitor and progressively improving activity and ADMET properties while maintaining good blood-brain barrier (BBB) penetration. The latter is important because inhibiting BACE1 is of interest as a way to treat Alzheimer’s disease, and compounds need to penetrate the blood-brain barrier to reach the target enzyme. This tutorial is based on the compounds prepared in the “Curating Data on BACE Inhibitors” tutorial plus some additional compounds not found in the data set described by Rombouts et al. (2015).

The tutorial is divided into 5 parts.

1. Loading the BACE1 inhibitor data set from an xtk file supplied with the program.

2. Loading two user models to use as AIDD optimization objectives.

3. Selecting a seed molecule from the BACE1 data set to use with AIDD.

4. Setting up the necessary AIDD run parameters, including choosing a set of objectives, defining a scaffold and specifying a filters file.

5. Running AIDD and then analyzing the results. The compounds generated will be compared to some of the compounds discussed by Rombouts et al. as well as to one of the ChEMBL compounds added to the AIDD data set.